Observation-based model for BDI-agents

  • Authors:

  • Kaile Su;Abdul Sattar;Kewen Wang;Xiangyu Luo;Guido Governatori;Vineet Padmanabhan

  • Affiliations:

  • Institute for Integrated and Intelligent Systems, Griffith University, Brisbane, Australia and Department of Computer Science, Sun Yat-sen University, Guangzhou, P.R.China;Institute for Integrated and Intelligent Systems, Griffith University, Brisbane, Australia;Institute for Integrated and Intelligent Systems, Griffith University, Brisbane, Australia;Department of Computer Science, Sun Yat-sen University, Guangzhou, P.R.China;School of ITEE, The University of Queensland, Brisbane, Australia;School of ITEE, The University of Queensland, Brisbane, Australia

  • Venue:
  • AAAI'05 Proceedings of the 20th national conference on Artificial intelligence - Volume 1
  • Year:
  • 2005

Quantified Score

Hi-index 0.00

Visualization

Abstract

We present a new computational model of BDI-agents, called the observation-based BDI-model. The key point of this BDI-model is to express agents' beliefs, desires and intentions as a set of runs (computing paths), which is exactly a system in the interpreted system model, a well-known agent model due to Halpern and his colleagues. Our BDI-model is computationally grounded in that we are able to associate the BDI-agent model with a computer program, and formulas, involving agents' beliefs, desires (goals) and intentions, can be understood as properties of program computations. We present a sound and complete proof system with respect to our BDI-model and explore how symbolic model checking techniques can be applied to model checking BDI-agents. In order to make our BDI-model more flexible and practically realistic, we generalize it so that agents can have multiple sources of beliefs, goals and intentions.